Abstract
One of the important fields in statistics is testing hypothesis of correlation coefficient. The extension of the idea of testing correlation to fuzzy hypothesis is of great interesting. In this study, we examined the use of fuzzy hypothesis testing approach for the Sequential Probability Ratio Test (SPRT) of correlation coefficient. Use of fuzzy hypothesis testing for correlation coefficient with SPRT is illustrated by an example.
Highlights
Correlation coefficient (ρ) is found to have applications in some area such as medicine, genetics, psychology, numerical taxonomy and quality control [1]
We examined the use of fuzzy hypothesis testing approach for the Sequential Probability Ratio Test (SPRT) of correlation coefficient
Use of fuzzy hypothesis testing for correlation coefficient with SPRT is illustrated by an example
Summary
Correlation coefficient (ρ) is found to have applications in some area such as medicine, genetics, psychology, numerical taxonomy and quality control [1]. Pradhan and Sathe [4] proposed an unbiased estimator of correlation coefficient This estimator suggested a SPRT for " " which reduces to an SPRT for the Bernoulli parameter , which is a simple function of, but two pairs of observations need each step. Torabi and Mirhosseini [9] introduced a SPRT for fuzzy hypothesis testing They developed fuzzy SPRT for testing the mean of Normal distribution with known variance and the parameter of Bernoulli distribution Akbari [10] proposed a new approach for SPRT of fuzzy hypothesis under density probability function. We apply SPRT to test fuzzy hypothesis for the correlation coefficient of a bivariate normal distribution. This method is demonstrated by an example.
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